Blog Pricing & Cost
DeepSeek V3 vs V4 Pro: Complete Comparison Guide
Compare DeepSeek V3 and V4 on API behavior, token economics, context, and migration considerations. Check live model availability before switching.
Pricing verified as of 2026-08-19. DeepSeek changed to peak/off-peak pricing on 2026-08-17.
Pricing updated 2026-08-19: AIWave V4 Flash is $0.30 input, $1.32 output, and $0.0203 cache hit; V4 Pro is $1.32 input, $3.96 output, and $0.044 cache hit per 1M tokens.
With multiple DeepSeek model variants available — V3, V3.1, V3.2, V4 Pro, V4 Flash, and R1 — choosing the right model for your project can be confusing. Here is what actually differs between them: architecture, price per million tokens, measured performance and the workloads each one suits.
DeepSeek Model Family Overview
| Model | Generation | Context | Best For | Status |
|---|---|---|---|---|
| DeepSeek V4 Pro | 4th gen (latest) | 128K | Best all-round performance | ✅ Recommended |
| DeepSeek V4 Flash | 4th gen | 128K | Fast, affordable inference | ✅ Recommended |
| DeepSeek R1 (Reasoner) | 4th gen | 128K | Chain-of-thought reasoning | ✅ Recommended |
| DeepSeek V3 | 3rd gen | 64K | Legacy applications | ⚠️ Being phased out |
| DeepSeek V3.1 | 3rd gen (refined) | 64K | Incremental V3 update | ⚠️ Legacy |
| DeepSeek V3.2 | 3rd gen (refined) | 64K | Minor V3 improvement | ⚠️ Legacy |
| ERNIE 4.0 (Baidu) | $1.32 | $0.55 | 128K |
Pricing Comparison
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Cost vs V4 Pro |
|---|---|---|---|
| DeepSeek V4 Pro | $1.32 | $3.96 | — (baseline) |
| DeepSeek V4 Flash | $0.30 | $1.20 | Lower AIWave list rate |
| DeepSeek R1 | $0.55 | $1.10 | 3.9x more |
| DeepSeek V3 | $0.27 | $1.10 | 1.9x more |
| GPT-4o (for reference) | $2.50 | $10.00 | 17.9x more |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
💡 Key finding: DeepSeek V4 Pro is nearly half the price of DeepSeek V3 ($1.32 vs $3.96/1M input) while delivering significantly better performance. There is no cost advantage to staying on V3.
Architecture & Performance
DeepSeek V3 Architecture
DeepSeek V3 uses a Mixture-of-Experts (MoE) architecture with 671B total parameters and 37B activated per token. It features a 64K context window, Multi-head Latent Attention (MLA), and was trained on 14.8T tokens. V3.1 and V3.2 are incremental refinements with minor alignment and safety improvements but share the same core architecture.
DeepSeek V4 Architecture
DeepSeek V4 represents a major architectural leap. Built on an improved MoE design with enhanced attention mechanisms, V4 Pro achieves significant gains in reasoning, coding, and multilingual performance while reducing inference costs. The 128K context window doubles V3's capacity.
Performance Benchmarks
| Benchmark | DeepSeek V4 Pro | DeepSeek V3 | Improvement |
|---|---|---|---|
| MMLU (knowledge) | 90.2% | 86.8% | +3.4% |
| HumanEval (coding) | 92.5% | 85.4% | +7.1% |
| MATH (reasoning) | 88.7% | 79.2% | +9.5% |
| Context Length | 128K | 64K | +100% |
| Inference Speed | ~40% faster | Baseline | +40% |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
V3 vs V4: Which Should You Choose?
Choose DeepSeek V4 Pro if you need:
- Best performance — V4 Pro outperforms V3 across all benchmarks, especially coding (+7.1%) and reasoning (+9.5%)
- Current pricing — Use the AIWave rate card updated 2026-08-19 and compare the exact V3 and V4 routes before changing a default.
- Larger context — 128K vs 64K gives you double the capacity for long documents
- Faster inference — Approximately 40% faster response times for production applications
Stick with DeepSeek V3 only if:
- You have a legacy integration that specifically requires V3
- You need backward compatibility with existing prompt engineering
- You're in the middle of a production rollout and can't switch mid-cycle
Consider DeepSeek V4 Flash for cost-sensitive workloads:
- At just $0.30/1M input tokens, V4 Flash is the great value DeepSeek model
- Ideal for high-volume, latency-tolerant applications like chatbots, content generation, and data processing
- Recalculate the token mix with the dated rate card before choosing a route.
What About V3.1 and V3.2?
DeepSeek V3.1 and V3.2 are minor updates to the V3 base model with alignment improvements, better instruction following, and safety updates. They do not introduce architectural changes and their performance is broadly similar to V3. For most users, upgrading directly from V3/V3.1/V3.2 to V4 Pro offers the best return on investment.
DeepSeek R1: The Reasoning Specialist
DeepSeek R1 (DeepSeek Reasoner) is a chain-of-thought reasoning model designed for complex multi-step problems. While V4 Pro handles most tasks efficiently, R1 excels at:
- Complex mathematical proofs
- Multi-step logical reasoning
- Scientific analysis and research tasks
- Advanced code debugging
At $0.55/1M input tokens, R1 is more expensive than V4 Pro but justified for tasks that require deep reasoning.
Quick Reference: When to Use Each Model
| Use Case | Recommended Model | Rationale | |
|---|---|---|---|
| General chatbot / assistant | DeepSeek V4 Pro | Best balance of quality and cost | |
| High-volume production API | DeepSeek V4 Flash | Workload-specific evaluation required. | |
| Complex math / logic problems | DeepSeek R1 | Chain-of-thought reasoning | |
| Code generation & review | DeepSeek V4 Pro | Top coding performance (+7.1%) | |
| Long document processing | DeepSeek V4 Pro or Kimi K2.5 | 128K or 200K context window | |
| Legacy V3 migration | DeepSeek V4 Pro | Drop-in upgrade, lower price | |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
Try DeepSeek V4 Pro Today
One API key for all DeepSeek models — V4 Pro, V4 Flash, R1, and V3.
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Frequently Asked Questions
Is DeepSeek V4 better than V3?
Yes. DeepSeek V4 Pro outperforms V3 across all benchmarks — especially coding, reasoning, and knowledge benchmarks — with a 128K context window and faster inference. The upgraded architecture also supports 128K context (up from 64K) and delivers ~40% faster inference.
Is DeepSeek V4 cheaper than V3?
Not always. Compare the current dated AIWave rate card, model quality, cache behavior, and workload before choosing a default.
What happened to DeepSeek V3.1 and V3.2?
V3.1 and V3.2 were minor refinements of the V3 base with alignment and safety improvements. They don't change the architecture or core performance. Users on any V3 variant should upgrade to V4 Pro.
What's the difference between DeepSeek V4 Pro and V4 Flash?
V4 Pro is the full flagship model with maximum performance. V4 Flash is a distilled variant optimized for speed and cost — a lower AIWave input rate than Pro ($0.30 vs $1.20, updated 2026-08-19) with slightly lower but still strong quality.
How does DeepSeek R1 compare to V4 Pro?
R1 (Reasoner) excels at chain-of-thought reasoning but is a separate reasoning route with different pricing and workload behavior. Use V4 Pro for general tasks and R1 specifically when you need step-by-step logical reasoning for complex problems.
What context window does each DeepSeek model support?
DeepSeek V4 Pro and V4 Flash support 128K tokens. DeepSeek R1 supports 128K tokens. DeepSeek V3 and all its variants (V3.1, V3.2) support 64K tokens.
References
Related: DeepSeek API pricing · DeepSeek V4 Pro
Test DeepSeek V4 Pro on your acceptance set, then compare the dated rate and request record.
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